A Pre-Gelled EEG Electrode and Its Application in SSVEP-Based BCI

Wu, Xiaoting; Zhang, Xiang; Zha, Aihua; Tian, Shen; Wang, Yijun; Gao, Xiaorong

doi:10.1109/tnsre.2022.3161989

Cited by 21 publications

(20 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, no differences in the characteristics of EEG signals acquired with caps with equidistant or extended ten-twenty layouts were observed. The applied EEG paradigm and signal metrics cover a broad range of signal characteristics allowing a comprehensive assessment of cap and electrode performance in line with metrics used in related previous studies [ 11 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ].…”

Section: Discussionmentioning

confidence: 99%

“…The performance of gel-based and dry EEG solutions has been compared by either sequential or simultaneous acquisition with both systems within application-specific paradigms. However, most comparative studies thus far comprise low numbers of volunteers and have been conducted in optimally controlled environments, such as shielded acquisition chambers [ 23 ] or focused on low-density EEG with dedicated electrode layouts and applications [ 3 , 4 , 5 , 24 , 25 , 26 ], including manual electrode placement and preparation [ 27 , 28 ]. Moreover, an important limitation of the majority of previous studies is the single-center and single-operator approach.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multi-Center Evaluation of Gel-Based and Dry Multipin EEG Caps

Fiedler

Kuhlmann

et al. 2022

Sensors

View full text Add to dashboard Cite

Dry electrodes for electroencephalography (EEG) allow new fields of application, including telemedicine, mobile EEG, emergency EEG, and long-term repetitive measurements for research, neurofeedback, or brain–computer interfaces. Different dry electrode technologies have been proposed and validated in comparison to conventional gel-based electrodes. Most previous studies have been performed at a single center and by single operators. We conducted a multi-center and multi-operator study validating multipin dry electrodes to study the reproducibility and generalizability of their performance in different environments and for different operators. Moreover, we aimed to study the interrelation of operator experience, preparation time, and wearing comfort on the EEG signal quality. EEG acquisitions using dry and gel-based EEG caps were carried out in 6 different countries with 115 volunteers, recording electrode-skin impedances, resting state EEG and evoked activity. The dry cap showed average channel reliability of 81% but higher average impedances than the gel-based cap. However, the dry EEG caps required 62% less preparation time. No statistical differences were observed between the gel-based and dry EEG signal characteristics in all signal metrics. We conclude that the performance of the dry multipin electrodes is highly reproducible, whereas the primary influences on channel reliability and signal quality are operator skill and experience.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-Center Evaluation of Gel-Based and Dry Multipin EEG Caps

Fiedler

Kuhlmann

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…To improve the practical utility of the BCI system, its ease of use can be improved in terms of EEG cap, standard monitor and the effort in reducing calibration time. Dry EEG cap [33] and pre-gelled EEG cap [34] are more practical and can be used to replace the gelbased EEG cap in real-world applications. A standard monitor can be employed for stimulus presentation in our future work to make the proposed BCI system more readily available.…”

Section: Discussionmentioning

confidence: 99%

A Spectrally-Dense Encoding Method for Designing a High-Speed SSVEP-BCI With 120 Stimuli

Chen

Liu

Wang

et al. 2022

IEEE Trans. Neural Syst. Rehabil. Eng.

Self Cite

View full text Add to dashboard Cite

The practical functionality of a braincomputer interface (BCI) is critically affected by the number of stimuli, especially for steady-state visual evoked potential based BCI (SSVEP-BCI), which shows promise for the implementation of a multi-target system for real-world applications. Joint frequency-phase modulation (JFPM) is an effective and widely used method in modulating SSVEPs. However, the ability of JFPM to implement an SSVEP-BCI system with a large number of stimuli, e.g., over 100 stimuli, remains unclear. To address this issue, a spectrally-dense JPFM (sJFPM) method is proposed to encode a broad array of stimuli, which modulates the lowand medium-frequency SSVEPs with a frequency interval of 0.1 Hz and triples the number of stimuli in conventional SSVEP-BCI to 120. To validate the effectiveness of the proposed 120-target BCI system, an offline experiment and a subsequent online experiment testing 18 healthy subjects in total were conducted. The offline experiment verified the feasibility of using sJFPM in designing an SSVEP-BCI system with 120 stimuli. Furthermore, the online experiment demonstrated that the proposed system achieved an average performance of 92.47±1.83% in online accuracy and 213.23 ± 6.60 bits/min in online information transfer rate (ITR), where more than 75% of the subjects attained the accuracy above 90% and the ITR above 200 bits/min. This present study demonstrates the effectiveness of sJFPM in elevating the number of stimuli to more than 100 and extends our understanding of encoding a large number of stimuli by means of finer frequency division.

show abstract

“…These dry electrodes operate with higher contact impedances and thus are more prone to artifacts than wet electrodes, which is partially compensated by higher input impedance amplifiers (Shad et al, 2020). There has been a lot of research in new conductive materials and electrode shapes to create novel dry-EEG electrodes: different conductive metals and coatings (Lopez-Gordo et al, 2014), hydrogels (Li et al, 2021; Pei et al, 2022), polymers (Leleux et al, 2014), conductive inks (Ferrari et al, 2020), graphene (Ko et al, 2021), organic transistors (Venkatraman et al, 2018), conductive/smart textiles (Tseghai et al, 2020), among others.…”

Section: Introductionmentioning

confidence: 99%

Garments that measure EEG: Evaluation of an EEG sensor layer fully implemented with smart textiles

López‐Larraz¹,

Escolano²,

Robledo³

et al. 2023

Preprint

View full text Add to dashboard Cite

This paper presents the first garment capable of measuring EEG activity with accuracy comparable to state-of-the art dry EEG systems. The main innovation is an EEG sensor layer (i.e., the electrodes, the signal transmission, and the cap support) fully implemented as a garment, using threads, fabrics and smart textiles, without relying on any metal or plastic materials. The garment is interfaced via a connector to a mobile EEG amplifier to complete the measurement system. The new EEG system (Garment-EEG) has been characterized with respect to a state-of-the-art Ag/AgCl dry-EEG system (Dry-EEG) over the forehead area of healthy participants in terms of: (1) skin-electrode impedance; (2) electrophysiological measurements (spontaneous and evoked EEG activity); (3) artifacts; and (4) user ergonomics and comfort. The results show that the Garment-EEG system provides comparable recordings to Dry-EEG, but it is more prone to getting affected by artifacts in adverse recording conditions due to poorer contact impedances. Ergonomics and comfort favor the textile-based sensor layer with respect to its metal-based counterpart. User acceptance is the main obstacle for EEG systems to democratize neurotechnology and non-invasive brain-computer interfaces. EEG sensor layers encapsulated in wearables have the potential to enable neurotechnology that is naturally accepted by people in their daily lives. Furthermore, by supporting the EEG implementation in the textile industry it is manufactured with lower cost and much less pollution compared to the metal and plastic industries.

show abstract

A Pre-Gelled EEG Electrode and Its Application in SSVEP-Based BCI

Cited by 21 publications

References 42 publications

Multi-Center Evaluation of Gel-Based and Dry Multipin EEG Caps

Multi-Center Evaluation of Gel-Based and Dry Multipin EEG Caps

A Spectrally-Dense Encoding Method for Designing a High-Speed SSVEP-BCI With 120 Stimuli

Garments that measure EEG: Evaluation of an EEG sensor layer fully implemented with smart textiles

Contact Info

Product

Resources

About